Dataset Optimization for Retrieval | Dataford Interview Questions

Write a function to optimize a given dataset for faster retrieval.

Interpret optimization as building an inverted index. The input is a list of records, where each record is a dictionary with a unique integer id and string text; ignore other fields. Return a dictionary mapping each lowercase alphanumeric token to a sorted list of record IDs containing that token. Treat repeated tokens within one record as one occurrence, and omit records with no tokens.

Function signature: def optimize_dataset(dataset):

Constraints

0 <= len(dataset) <= 5000
Each record has a unique integer id and a string text field
Record IDs are between -10^9 and 10^9
The total text length is at most 1,000,000 characters
Tokens consist of contiguous ASCII letters and digits
Tokens are compared case-insensitively
Records with empty or punctuation-only text contribute no index entries

Function Signature

def optimize_dataset(dataset):

Your question is Dataset Optimization for Retrieval. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.

Problem

Write a function to optimize a given dataset for faster retrieval.

Function signature: def optimize_dataset(dataset):

Constraints

0 <= len(dataset) <= 5000
Each record has a unique integer id and a string text field
Record IDs are between -10^9 and 10^9
The total text length is at most 1,000,000 characters
Tokens consist of contiguous ASCII letters and digits
Tokens are compared case-insensitively
Records with empty or punctuation-only text contribute no index entries

Function Signature

def optimize_dataset(dataset):

Your question is Dataset Optimization for Retrieval. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.